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Title: Linear Programming Model for Estimating High-Resolution Freeway Traffic States from Vehicle Identification and Location Data
Accession Number: 01519176
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: The estimation of traffic state on freeway segments is widely studied as a complex nonlinear and stochastic estimation problem. A unified representation with a parsimonious explanation for traffic observations under free-flow, congested, and dynamic transient conditions is developed by capturing the essential characteristics of forward and backward wave propagation through cumulative flow count variables. New formulations are presented to use Bluetooth vehicle identification records and GPS vehicle location data on a freeway corridor with a merge and diverge. With the addition of nonnegativity and maximum discharge rate constraints, a computationally efficient linear programming model is constructed to estimate traffic states (i.e., density and traffic flow) from cumulative flow counts at each second. The proposed model is implemented and tested systematically on the basis of a real-world next generation simulation (NGSIM) data set.
Monograph Title: Monograph Accession #: 01541211
Report/Paper Numbers: 14-5449
Language: English
Authors: Lei, HaoZhou, XuesongPagination: pp 151–160
Publication Date: 2014
ISBN: 9780309295154
Media Type: Print
Features: Figures
(8)
; References
(26)
; Tables
(1)
TRT Terms: Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning
Files: TRIS, TRB, ATRI
Created Date: Jan 27 2014 3:55PM
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